With Dr. Irina Rish (AI Foundations Lab, IBM T.J. Watson Research) and GoodAI
Quantifying mental states and identifying statistical biomarkers of mental disorders from neuroimaging data is an exciting and rapidly growing research area at the intersection of neuroscience and machine learning, with the particular focus on interpretability and reproducibility of learned models. We discussed promises and limitations of machine-learning methods in applications involving fMRI and EEG data; moreover, we summarized some directions related to mental state inference “beyond the scanner,” involving speech and wearable sensors, with applications ranging from clinical settings (“computational psychiatry”) to everyday life (“augmented human”).
Finally, besides the above “AI to Brain” direction, we discussed “Brain to AI,” namely, borrowing ideas from neuroscience to improve machine learning, with specific focus on adult neurogenesis and online model adaptation in representation learning.
In this meetup, Dr. Rish explored the intersection of neuroscience and machine learning, and a general artificial intelligence R&D company GoodAI will introduce its $5M General AI Challenge, aiming to tackle crucial research problems in human-level AI development.
Wednesday, May 3, 6.p.m.
WeWork Park South 10th Floor Lounge (entrance at 110 E. 28th Street)